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. 2024 Aug 19;63(2):148–155. doi: 10.2486/indhealth.2024-0088

The relationship between shift work, sleep, and work hours on wellbeing

Lee DI MILIA 1,*, Bjorn BJORVATN 2,3
PMCID: PMC11995149  PMID: 39155078

Abstract

We investigated the role of sleep and work hours on wellbeing among day- and shift workers. We tested a mediation-moderation hypothesis proposing that; 1) sleep would mediate the association between the work schedule and the impact of sleep/sleepiness on wellbeing; 2) work hours would moderate the link between work schedule and sleep. We made random phone calls to 1,162 participants and identified 172-d and 130 shift workers that worked ≥35 h/week. The work schedule had a positive indirect effect on the impact of sleep/sleepiness via sleep duration (β=0.0511, SE=0.0309, [0.0008, 0.3219]. The relationship between shift work and sleep duration was negative (β=−0.35, SE=0.14, p<0.01), and sleep duration was negatively associated with a greater impact of sleep/sleepiness on wellbeing (β=−0.15, SE=0.06, p<0.02). The path between the work schedule and sleep duration was moderated by work hours; fewer work hours resulted in shift workers reporting a greater impact of sleep/sleepiness on wellbeing. The results support the mediation-moderation hypothesis. Work hours and sleep duration are key characteristics in work schedule design.

Keywords: Shift work, Sleep, Work hours, Wellbeing

Introduction

The needs of industry and community expectations for services such as healthcare and telecommunications require some workers to operate around the clock. Shift work refers to work schedules that are designed to provide coverage for more than an 8-h day and up to a 24-h period1). The design of shift work systems can take many forms2) but to reduce this complexity, the literature defines shift work as working arrangements that occur outside of ‘ordinary’ hours, which are usually defined as between 06:00 and 18:003, 4). Estimates suggest some 15% of Australian5), 21% of European6), and 16% of North American workers7) undertake some form of shift work.

A comprehensive theoretical model of shift work proposes that night work causes circadian disruption, disturbed sleep, and greater psychosocial stress. In turn, these factors are associated with neuroendocrine, cardiometabolic and cellular stress, altered immune function, and cognitive impairments8). There is ample evidence linking shift work with several impairments. Some 16% of night workers compared to day workers, were considered more likely to develop hypertension, diabetes, coronary heart disease and stroke. In addition, these data suggested this risk increased with greater exposure to night work9). Recent data concluded that shift work regardless of whether night work is involved was associated with an increased risk of breast cancer for women over 50 yr of age10).

The literature routinely reports that night work is associated with higher levels of sleepiness, and difficulties with initiating and maintaining sleep following night work11). The two-process model of sleep regulation12) suggests that sleep during the day is problematic given the conflict between the circadian process (a drive for wakefulness during the day), and the sleep-wake homeostasis process placing increasing pressure for sleep given the amount of time a worker is awake. A meta-analysis of sleep duration found that the longest sleep duration was associated with evening shifts (some 8 h) and the least amount of sleep (<6 h) was obtained following night shifts13). Another meta-analysis concluded that shift workers had a higher chance of developing sleep disturbances14), and a regular finding is that night workers report more fatigue and require more recovery sleep on days off15). The last decade has seen much interest in ‘shift work disorder’—a condition exemplified by excessive sleepiness and complaints of insomnia that is attributable to the work schedule. A recent meta-analysis of this literature estimated the prevalence rate of shift work disorder at 26.5%16) and other studies report that the rate of objectively prescribed medication is greater among shift workers with night work, compared to shift work without night work17).

While there is plenty of evidence to suggest night work is associated with acute sleep difficulties and shorter sleep duration, it is less clear if night workers face chronic sleep impairments over successive work cycles and whether the night shift per se, is the main factor. Long term longitudinal studies of sleep among shift workers are required to address the question of chronic sleep deprivation, and these studies were not found in a recent Cochrane review of shift work schedules and sleep18). In a large representative study of Swedish workers undertaking a variety of work schedules, negative attitudes to working arrangements were reported by 6% of permanent night shift workers and 21% of shift workers that included night work19). Nonetheless, some 50% of shift workers who worked night shifts, reported sleep impairments and fatigue.

The discussion suggests that shift and night work is associated with several sleep impairments, but on the other hand, worker attitudes to night work are generally positive19). Given the importance of obtaining adequate sleep, it is reasonable to posit that the work schedule may not be the critical factor in determining its relationship with wellbeing, but rather that sleep duration may play a mediating role. This argument leads to the following hypothesis.

H1: The relationship between a work schedule and the impact of sleep/sleepiness on wellbeing (i.e. on social, family and work satisfaction) is mediated by sleep duration.

Another important variable in the design of work schedules is work hours. The association between time on shift and fatigue is not monotonic, yet the literature routinely reports concerns over long work hours and night work20, 21). A recent review of 220 studies concluded that shift work and long work hours are associated with poor sleep, greater fatigue, absence from work and occupational injuries other chronic health conditions20). In a study of 31,627 nurses across twelve European countries, nurses working 12-h shifts experienced greater emotional exhaustion (OR=1.26), feelings of depersonalisation (OR=1.21, less personal accomplishment (OR=1.39), and less job satisfaction (OR=1.40) compared to nurses on 8-h shift21). In a follow up study, having ‘choice’ over longer shifts did not moderate these findings22). A British longitudinal study reported that working ≥55 h per week was associated with less daily sleep (<7 h) and more sleep disturbances compared with working a 35–40-h week23). Recent findings also suggest that long work hours (≥56 h) are linked with a 13% increase in the use of sedative-hypnotic drugs24) and a study of 26,000 office workers, found that overtime was linked with nonrestorative sleep25).

We have argued that long work hours and sleep seem inversely related, but the relationship is more complex. The non-work environment also places pressure on workers to do more than sleep and work. Shift workers need to make time for parenting, partner support and social activity26). Evidence shows that shift workers reporting higher levels of work-life conflict indicated a preference to leave their job27). Mid-life adults are typically combining work and family roles placing pressure on sleep time. Data from the American Time Use Survey (ATUS) reveals a U-shaped distribution showing that the least sleep is obtained by males and females in the 45–54 age group, followed by the 34–44 age group28). One observation from the ATUS is that sleep is sacrificed to accommodate other demands29).

The argument that shift workers may need to trade sleep for other demands suggests that work hours may have a different effect on sleep duration in this group. Whereas one may predict that fewer work hours will increase sleep, paradoxically, it may be that when work hours are low, shift workers obtain less sleep to meet family and social demands. However, when shift workers work longer hours, the associated fatigue and accumulated sleep loss results in more pressure for longer sleep15). This reasoning leads to our second hypothesis for this study.

H2: The relationship between work schedules and sleep duration is moderated by work hours such that shift workers working fewer hours report a greater impact of sleep/sleepiness on wellbeing.

The first hypothesis suggests that sleep duration plays a mediating role between the work schedule and the impact of sleep/sleepiness, and the second hypothesis, argues that work hours will moderate the relationship between the work schedule and sleep duration for shift workers. The combination of mediation and moderation pathways is summarised in Fig. 1 which suggests a conditional indirect effect30) between the variables. This reasoning forms the third hypothesis.

Fig. 1.

Fig. 1.

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Conceptual model.

H3: Work hours moderate the indirect effect of work schedules on the impact of sleep/sleepiness on wellbeing via sleep duration such that the indirect effect is stronger when shift workers complete fewer work hours.

Participants and Methods

The study is a subset of a larger study that collected data on physical fitness, health, working arrangements and wellbeing. Random sample phone calls were made to 1,162 participants in three regional cities in Australia. Trained interviewers asked to speak to participants in full time employment over 18 yr of age. Participants were informed that their participation was anonymous, voluntary, confidential and they could cease participation at any time during the interview. The interview lasted some twenty-six minutes. Participants provided verbal agreement given the inability to obtain written agreement. The study was approved by the human research ethics committee at Central Queensland University (H11_09_149).

Instruments

The survey collected demographic and other data that were used to construct the following variables.

Work schedule - Participants were asked whether they worked primarily during the day (i.e. between 07:00−18:00) or some form of shift work. Those that reported starting and completing work within these hours were categorised as ‘day workers’. Those that reported working shifts were asked to confirm whether they: (1) worked during the day, and (2) whether they commenced and ended a shift between 18:00 and 07:00. Participants that met both conditions were categorised as ‘shift workers’.

Work hours – participants reported their typical weekly working hours.

Sleep duration – participants reported their usual daily sleep duration.

Job satisfaction – participants reported overall satisfaction with their job considering income, working conditions, coworkers, and supervisors (1=very dissatisfied; 5=very satisfied).

Impact of sleep/sleepiness − participants responded to the following question − “to what extent does your sleep or sleepiness problem negatively affect your social, family or work relationships?” (1=not at all, 5=very much).

Control variables. Analyses were controlled for; age, sex, body-mass-index (weight divided by height squared), and job satisfaction given these variables are associated with the independent and dependent variables.

Data analysis strategy

Data were analysed using SPSS (V28.0). A multivariate analysis of variance was used to test for differences between the work schedule and sex, on the variables of interest. To plot the interaction between work schedule, work hours and sleep duration, the control and independent variables were mean centred31) and these variables were used to produce the coefficients using a two-step hierarchical regression model.

PROCESS macro for SPSS (V4.2) was used to conduct the moderation-mediation analysis. PROCESS employed 5,000 bootstrap samples and the bias corrected confidence intervals (CI) were set at 95% to assess the conditional indirect effects30). CIs that exclude a zero value indicate a significant result.

Results

Four hundred and eighty participants responded to the survey, and we deleted participants working less than 35 h per week (n=302). The sample consisted of 172-d workers (90 females) and 130 (42 females) shift workers. A chi-square test indicated males were significantly more likely to be shift workers (χ2= 12.06, p<0.001). The participants were drawn from a wide range of industry sectors; the three main sectors were mining (15.20%), health and community services (14.60%), and transport (13.60%).

Descriptive statistics and correlations can be found in Table 1. Mean age (46.21, SD=10.74) did not differ by sex or work schedule. Males worked 47.35 h/week (SD=8.84), compared to females (M=42.15, SD=7.28; p<0.001) but no sex differences were found for sleep duration, the impact of sleep/sleepiness or job satisfaction. Significant differences were obtained between the work schedule and sleep duration (day workers; M=6.91, SD=1.15; shift workers; M=6.51, SD=1.21, p<0.01), the impact of sleep/sleepiness on wellbeing (day workers; M=2.66, SD=1.26; shift workers; M=3.02, SD=1.38, p<0.05) and work hours (day workers; M=43.90, SD=7.70; shift workers; M=46.63, SD=9.41, p<0.01).

Table 1. Descriptive statistics and correlations for study variables.

Mean SD 1 2 3 4 5 6 7
1. Age 46.21 10.74
2. Job satisfaction 3.80 1.05 0.23
3. BMI 29.00 5.90 0.16** −0.14*
4. Sex† – – −0.09 −0.02 0.05
5. Work schedule‡ – – 0.08 −0.10 0.11 0.20**
6. Work hours 45.07 8.57 −0.09 0.01 0.08 0.30** 0.16**
7. Sleep duration 6.74 1.19 −0.17** 0.06 −0.06 0.00 −0.17** −0.10
8. Impact of sleep/sleepiness 2.81 1.32 0.01 −0.26*** 0.03 0.04 0.13* 0.02 −0.16**
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†0=female, 1=male, ‡0=day, worker 1=shift worker.

*p<0.05, **p<0.01, ***p<0.001.

BMI: body mass index.

Job satisfaction and the impact of sleep/sleepiness were negatively correlated. No association was found between job satisfaction and work schedule. The categorical nature of biserial correlations obscured some correlations. The relationship between work hours and sleep duration in day workers was −0.24 (p<0.001) and 0.09 for shift workers.

The regression results can be found in Table 2. Overall, the work schedule had a positive indirect effect on the impact of sleep/sleepiness via sleep duration (β=0.0511, SE=0.0309, [0.0008, 0.3219]. The relationship between night work and sleep duration was negative (Model 1: β =−0.35, SE=0.14, p<0.01), and sleep duration was also negatively associated with the impact of sleep/sleepiness (Model 2: β =−0.15, SE=0.06, p<0.02).

Table 2. Hierarchical and moderated regression analyses (unstandardized coefficients).

Mediation Moderation
Model 1 (Mediator: sleep duration) Model 2 (Outcome: impact of sleep/sleepiness) Model 3 (Work schedule × work hours → sleep duration)
B SE p B SE p B SE p
Constant 7.56 0.53 0.000*** 5.32 0.75 0.000*** 9.13 0.72 0.000***
Control variables
Age −0.02 0.01 0.01*** −0.00 0.01 0.57 −0.02 0.01 0.01**
Job satisfaction 0.04 0.07 0.54 −0.32 0.07 0.000*** 0.04 0.07 0.57
BMI −0.00 0.01 0.84 −0.01 0.01 0.54 −0.00 0.01 0.93
Sex† 0.06 0.14 0.69 0.04 0.15 0.81 0.15 0.14 0.31
Work schedule‡ −0.35 0.14 0.01** 0.24 0.16 0.13 −2.21 0.74 0.00***
Work hours −0.04 0.01 0.00***
Sleep duration −0.15* 0.06 0.02*
Work schedule × work hours 0.04* 0.20 0.00**
Indirect effect of work schedule on sleep impact via sleep duration Boot B Boot SE 95% bias-corrected CI
0.0511 0.0309 [0.0009, 0.3219]
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†female=0, male=1; ‡day=0, Irregular=1.

*p<0.01, **p<0.01, ***p<0.001.

The results suggested that work hours moderated the relationship between work schedule and sleep duration (see Model 3: β =0.04, SE=0.20, p<0.01). The interaction between these variables can be found in Fig. 2. Simple slopes analysis indicated that the effect of work schedules on sleep duration was negative when working hours were low (slope=−0.69, t =−3.41, p<0.001) but not when working hours were high (slope=0.03, t=−0.14, p<0.89). Sleep duration in day workers showed a marked decrease as their working hours increased (Fig. 2). The index of moderated mediation was significant (β =−0.0061, SE=0.0040, CI=[−0.0152, −0.0003] and provides support for the presence of a mediated-moderation relationship.

Fig. 2.

Fig. 2.

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The interaction effect of work schedule and working hours on sleep duration.

Discussion

Studies demonstrate that shift work and long working hours are associated with shorter sleep duration11), more sleep disturbances14), fatigue15), a higher prevalence of shift work disorder16), and greater absences and injuries20). These outcomes are concerning given the literature shows that sleep plays a fundamental role in supporting physiological and psychological wellbeing32).

Notwithstanding, the negative impact of shift work on several outcomes, worker attitudes to shift work seem to be positive with one study reporting only 21% of workers are dissatisfied19). Building on this argument that the work schedule may not be the main problem per se, we first proposed that sleep duration would mediate the relationship between the work schedule and the impact of sleep/sleepiness on wellbeing. The results supported this hypothesis. Shift workers obtained less sleep and in turn, the lack of sufficient sleep had a negative impact on wellbeing. The key point is that the result was not the outcome of the work schedule itself, but the amount of sleep obtained. The second hypothesis argued that the path between work schedules and sleep duration would be moderated by working hours and the results supported this position. However, we argued a paradoxical position such that when working hours were less, shift workers reported less sleep, and this increased the impact on their wellbeing. Less working hours in the day group was not problematic, but greater working hours in both groups increased sleep/sleepiness (Fig. 2).

Working hours are a critical feature of work schedule design because they can assist with rest, recovery, and free time for family and/or social demands26). However, our results did not support this argument in our shift work group. We suggest that when shift workers have more time, they allocate this time to family and friends, at the expense of sleep. Alternatively, when they work longer hours, the associated fatigue and prior sleep loss, means they allocate more time for sleep15).

Work hours also played a role in how day workers used their time. Unlike the shift work group, we found a negative relationship between work hours and sleep duration in the day work group (−0.24) and this estimate compared favourably with a similar finding (−0.36) from the ATUS28). One interpretation of this relationship is that day workers also reduce their sleep duration to allow for other priorities such as domestic and childcare duties. Time is a fixed commodity such that every additional hour of work in the ATUS was associated a 14-min reduction in sleep time29).

These findings have some implications for work schedules. Long work hours are linked with work schedule dissatisfaction20), emotional exhaustion21, 22) and sleep disturbances19, 23). A recent review called on reducing work hours to minimise the social and family impact of shift work26). Our results suggested fewer work hours did not benefit the shift workers in terms of sleep duration or wellbeing, but fewer work hours may help to reduce fatigue15), for example. Fewer work hours were beneficial for day workers given they were associated with longer sleep duration and consequently, wellbeing. We suggest other work schedule characteristics may be useful for shift workers. For example, the number of work and days off across the work cycle to limit chronic sleep loss and social isolation and providing education to assist shift workers to better balance sleep need against family and social demands. We encourage long term multi-wave studies that allow a deeper understanding of how sleep and time are used by workers to manage competing demands.

The shift work literature is centred on a quandary. On one hand, shift work is associated with several impairments20) but on the other hand, not all shift workers are equally impacted by circadian disruption. For example, shift work disorder16) does not affect most shift workers, and not all workers hold negative attitudes to night work19). Evidence is accumulating that some workers are tolerant to the demands of night work33) and others, may accept shift work for the benefits it provides, such as better pay and time off when others are at work. These conflicting viewpoints make it difficult to educate night shift workers of the associated health and safety risks. Nonetheless, it is important that workers are provided with occupational health recommendations. In this regard, there is a shift from ‘prescriptive rules’ that for example, limit the length of a work shift or the number of consecutive shifts34), to risk management strategies that recognise that workplaces are not homogenous. Examples of these strategies include, designing shifts that allow for sufficient sleep time, workplace fatigue risk detection to alert employees and supervisors of a potential event, and training programs to assist workers to maximise recovery time from work35). Recommendations to limit social and family disruption suggest limiting shift length and evening/weekend work and to include some control over work hours26). The challenge may be in how well the literature can communicate the recommendations, and in turn, having employees follow these recommendations. For example, a review of sixteen studies concluded shift workers use caffeine to be alert during night shift but used alcohol to facilitate morning sleep onset36). An online study of Australian workers found that 53% were aware of ‘sleep hygiene’ and they were more likely to engage in good practices such as creating a dark and cool space for sleep37).

A strength of this study is that the sample was randomly selected, and thus, the results may have wider generalisability because they are not prone to occupational specific characteristics. Another strength is that the sample was in full-time employment and therefore, the mean sleep duration and working hours estimates were not influenced by part-time employees. The hypotheses were tested using bootstrapping which is considered a rigorous approach to testing indirect effects and generates more accurate results38). However, there are some limitations to note. The study employed a cross-sectional design, and this prevents the ability to make causal inferences. Consistent with many large-scale studies the data were all self-reported and this raises the possibility of bias. Our estimate of sleep duration was subjectively assessed with a single item, and some literature suggests these estimates are inflated compared to polysomnography. Recent studies suggest this argument requires some refinement. For example, Benz et al.39) reported that good sleepers over reported their subjective sleep (assessed via a single item from the Pittsburgh Sleep Quality Index40) and sleep diary) compared with polysomnography, while insomnia sufferers under reported subjective sleep. Finally, we categorised shift workers in line with contemporary definitions3, 4) yet the possibility exists that some participants may have only worked a few hours into the evening, rather than into the early morning hours. We suggest this is unlikely because this group worked long weekly hours (M=46.63; range 35−75 h), slept less than the day workers, and reported a greater impact from the associated sleep/sleepiness with the schedule. In response to these limitations, we make some recommendations for future studies; to employ a longitudinal design and obtain objective indicators where possible such as polysomnography and payroll records to verify working hours. We also suggest that future studies include fatigue as a covariate in any replication of our study. Fatigue refers to the tiredness associated with a completing a work shift and results suggest night work is associated with higher levels of fatigue15).

To summarise, the results suggest that the work schedule was not directly linked with the impact of sleep/sleepiness on wellbeing. Rather, the results suggested an indirect link whereby sleep duration mediated the relationship such that night workers obtained less sleep, and this resulted in a greater impact of sleep/sleepiness. In addition, the path between the work schedule and sleep duration was moderated by work hours. Reducing work hours in shift workers was not associated with longer sleep duration.

Author’s Contributions

LDM designed the study, conducted analyses, and drafted the manuscript. BB reviewed the results, provided extensive feedback on the draft manuscript, and cowrote the final submission. Both authors approved the final submission.

Data Availability

The data is available from the corresponding author without undue reservation.

Conflict of Interest

The authors declare no conflicts of interest.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data is available from the corresponding author without undue reservation.

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